Himanshu Sangshetti
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Library Articles
How to Enable Memory in Your Agentic Stack with a Single Command
mem0 init --agent --json provisions a Mem0 API key in under 5 seconds. No email, no browser. Includes LangGraph and CrewAI integration snippets.
The Easiest Way to Add Persistent Memory to Any AI Agent
Add persistent memory to any AI agent - LangGraph, CrewAI, Claude Code, Cursor, or a CI/CD pipeline - with one command. No manual API key setup, no SDK boilerplate.
Agent Models And Memory First Architectures
Explore memory-first agent architectures: how agents that retrieve, reason, and checkpoint memory outperform stateless alternatives at scale.
Vector Databases vs. Memory Layers for AI Agents
A vector database stores embeddings. It doesn't extract facts, resolve conflicts, or know what to forget. Here's what a real memory layer for AI agents adds - and when you need one.
Agentic workflows with Persistent Memory
Agentic workflows lose context between runs by default. Learn how persistent memory keeps agents informed across sessions using Mem0 and LangGraph.
Message Indexing And Memory Capture For AI Agents
Raw message indexing accumulates noise. Learn how extraction-first memory capture gives AI agents precise, deduplicated context from conversation history.
How Memory Works In Agent-to-Agent Protocols
When agents hand off tasks to other agents, memory does not transfer automatically. Learn how shared memory works across agent-to-agent protocols.
AI Memory Benchmarks: LoCoMo vs. LongMemEval vs. BEAM
Know what AI memory benchmarks are and see the 2026 LoCoMo, LongMemEval, and BEAM leaderboard: Mem0 scores 92.5% / 94.4% / 64.1%, plus how Zep, ByteRover, Dakera, and others compare.
Semantic Memory for AI Agents: Facts, Relationships
Semantic memory: durable facts, relationships, preferences. How extraction, scoping, and decay work in AI agents.
Memory eviction and forgetting in AI agents
Whar is memory eviction, why an agent that remembers everything recalls badly and how to design forgetting on purpose.
Episodic Memory in AI Agents: How It Works and Why It Matters
What is episodic memory in AI agents, why it matters, and how to wire it through Mem0 - with a comparison against Letta, Zep, and LangChain.
Working memory for AI agents
What working memory means for AI agents, why a context window is not the same thing, and how to design for it.
OpenClaw vs. Hermes Agent Memory in 2026: Which Should You Choose?
OpenClaw and Hermes take opposite bets on agent memory - live-injected vs. frozen snapshots, file-based vs. structured tools. Here's how each works, where each breaks, and how Mem0 fits both.
How Memory works in Hermes Agent (and how to improve it)
How Hermes Agent stores 3,575 characters of memory in two frozen markdown files, and where the design breaks.
Memory Layer for Open Source Agent Frameworks
Learn how LangGraph, AutoGen, CrewAI, and LangChain handle memory natively and how to add persistent, cross-session user memory with Mem0.
FastMCP tools with Shared Memory for AI Agents
FastMCP makes building MCP tools straightforward. Learn how to add shared persistent memory across MCP tool calls using Mem0.
Persistent Memory for Claude Agents SDK
The Claude Agents SDK tracks session state but not user context across sessions. Learn how to add persistent, per-user memory with Mem0.
How to add memory to LangGraph Agents
Learn how to add persistent, per-user memory to LangGraph agents with Mem0.
How to add memory to LlamaIndex agents
Step-by-step guide to adding persistent, cross-session memory to LlamaIndex agents using Mem0.
How to add Memory to Langchain Agents
Step-by-step guide to adding persistent, cross-session memory to LangChain agents using Mem0.